Tag: embedded systems
Episode 80: OSGi with Peter Kriens and BJ Hargrave
This episode is about OSGi, the dynamic module system for Java. Our guests are Peter Kriens (OSGI’s Technical Director) and BJ Hargrave (OSGI’s CTO). We’ll discuss what OSGi is all about and why and in which contexts it is useful. Additionally we are having a look at the different layers of OSGI and where and how they are used. Other questions discussed are: What means dynamicity in an OSGI environment? Where is OSGI used? What’s the future of OSGI? How does OSGI interact with existing middleware solutions? How can I run several versions of the same JAR at the same time? Where are OSGI’s problems?
Episode 79: Small Memory Software with Weir and Noble
In this Episode we’re discussing patterns for small memory software with the authors of the like-named book Charles Weir and James Noble. We look at various aspects of the small memory problem: How can you manage memory use across a whole system? What can you do when you have run out of primary storage? How can you fit a quart of data into a pint pot of memory? How can you reduce the memory needed for your data? How do you allocate memory to store your data structures? Answers to all those questions are provided in this Episode, and of course in their book.
Episode 78: Fault Tolerance with Bob Hanmer Pt. 2
This is the second part of the discussion on fault tolerance with Bob Hanmer (if you didn’t listen to Episode 77, which contains part one, please go back and listen now; this episode builds on that previous one!)
We start by discussing a set of error detection patterns. Among are the well-known approaches such as checksums and voting. We then look at error recovery patterns, including restart, rollback or roll forward. The next section looks
at error mitigation patterns, which include shedding load and doing fresh work before stale. The last patterns section then looks at fault treatment patterns.
We conclude the episode with a small discussion about how to design systems using (these and other) patterns, and with some thoughts on why actually wrote the book.
Episode 77: Fault Tolerance with Bob Hanmer Pt. 1
In this Episode we discuss fault tolerance based on the new book by Bob Hanmer. This is the actually the first part of the discussion, the remainder will be published in the next episode of SE Radio.
We start by discussing some of the context for fault tolerant systems and the imperfect world assumption. We then discuss a number of terms we will need when discussing the fault tolerance patterns. We then discuss the fault tolerance mindset and connect fault tolerance to a number of related subject areas, such as software quality. We then discuss the shared context for the patterns that follow, among them the important observation that fault tolerance does not come for free!
Finally we provide an overview over the different sections covered in the book and start the detailed discussion of the patterns by looking at the Architectural Patterns section.
The next episode will discuss the remaining patterns in the book.
Episode 73: Real Time Systems with Bruce Powel Douglass
This episode is a conversation with Bruce Powel Douglass on real time systems. We started by discussing what real time software is, and explored the difference between hard and soft real time. We then looked at different scheduling strategies, and the meaning of terms like urgency and importance in the context of scheduling. Next was a discussion of typical architectural styles for real time systems and how architectures are described in this context. This led us to a discussion about the importance of modeling, formalisms and languages as well as the role of automatic code generation from those models. We then looked at how to model QoS aspects and the role of SysML for modeling real time systems. We then had a brief look at which programming languages are used these days for real time systems and the role of static analysis to determine various properties of those programs in advance. The last part of the discussion focused on some best practices for building real time systems, the challenges in distributed real time systems and how real time systems can be tested effectively.
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